Ndị klas nke Naive Bayes
Naive Bayes bụ ngwa ngwa, nhazi ọkwa nke puru omume wuru na Bayes' theorem nke na-eche na njirimara ọ bụla nwere onwe ya nyere klas ahụ.
Nchịkọta
Despite that unrealistic assumption, it works remarkably well for text tasks like spam filtering.
Ime miri emi
Naive Bayes tụgharịrị nhazi ọkwa ka ọ bụrụ ngụkọta nke puru omume. Iji Bayes' theorem, ọ na-atụle ihe gbasara puru omume nke klaasị nyere atụmatụ ntinye, wee họrọ klaasị nwere akara kacha elu. Akụkụ 'naive' bụ echiche ya na atụmatụ niile nwere onwe ha nyere klas ahụ, yabụ ọ nwere ike ịmụba ohere njirimara nke ọ bụla kama ịmegharị mmekọrịta ha. Nke a na-ebelata nke ukwuu data na mgbakọ dị mkpa. Ụdị dị iche iche a na-ahụkarị gụnyere Multinomial Naive Bayes (ọnụọgụ okwu na akwụkwọ), Bernoulli Naive Bayes (okwu dị ugbu a/adịghị adị), na Gaussian Naive Bayes (atụmatụ na-aga n'ihu nke ejiri nkesa kwesịrị ekwesị mee). Ọ na-azụ n'otu ngafe na data ahụ, ọ chọrọ obere nlegharị anya, ma na-ejikwa ọtụtụ puku njirimara mara mma, nke mere ka ọ bụrụ usoro ihe ndabere maka nchọpụta spam na nhazi akwụkwọ.
Nghọta nka nka
Maka klaasị c na njirimara x1..xn, ọ na-agbakọ P(c) ugboro ngwaahịa P(xi|c), wee na-emeziwanye ya. N'ihi na ịmụba ọtụtụ obere ihe gbasara omume na-ebute mbelata ọnụọgụ ọnụọgụgụ, mmejuputa atumatu nchikota log-probabilities kama. Laplace (gbakwunye-otu) ire ụtọ na-egbochi otu okwu a na-adịghị ahụ anya ịpụpụ ngwaahịa ahụ dum. A na-eme atụmatụ P(xi|c) na P(c) nke bu ụzọ site na ngụkọ dị mfe site na usoro ọzụzụ, ya mere ọzụzụ ji bụrụ naanị ịgụta ugboro ole.
Mmetụta atụmatụ
Mkpebi doro anya
Ọ na-enyere gị aka ikewapụta nkwupụta ọrụ aka doro anya na asụsụ ahịa.
Ọnụ ego na mmefu ego
Ị nwere ike ịjụ ajụjụ mmejuputa iwu ka mma tupu itinye ego ma ọ bụ oge.
Team na usoro ọrụ
Ndị otu nwere nghọta na-eme ka ngwaahịa, amụma na mkpebi mmụta ka mma.
Ọdịnihu nke ndị klas Naive Bayes
Netwọk akwara dị omimi na ihe ntụgharị na-achịkwa nhazi ederede, yabụ Naive Bayes anaghị adịkarị onye na-eme ihe ngosi. Mana ọ na-atachi obi dị ka ntọala siri ike, dị nso ngwa ngwa, ngwa nkuzi nwere ike ịkọwa, yana nhọrọ bara uru mgbe data dị ụkọ, nkwụsị ga-adị ntakịrị, ma ọ bụ gbakọọ nwere oke. Na-atụ anya na ọ ga-anọgide na-agbakwunyere na nzacha ngwaọrụ dị fechaa, pipeline na-eme ngwa ngwa, yana sistemu ngwakọ ebe ụzọ nhazi ụzọ ngafe mbụ dị ọnụ ala na-ebute tupu akpọkuo ụdị dị arọ karị.
Mmejuputa n'ezie n'ụwa
Ihe nzacha spam email na-enweta akara ozi site na mkpụrụokwu ha nwere
Ntụle mmetụta uche na-akpado nlebanya ngwaahịa dị ka ihe dị mma ma ọ bụ adịghị mma
Na-ebugharị tiketi nkwado ma ọ bụ akụkọ akụkọ n'ime edemede isiokwu
Nchọpụta asụsụ na nhazi akwụkwọ dị mfe na pipeline ọchụchọ
Ihe ize ndụ & okporo ụzọ nche
Otu dị iche iche nwere ike iji otu okwu ahụ mee ihe n'ụzọ dị iche, yabụ kọwapụta oge n'oge.
Ihe nrịbama nwere ike ịdị ike ebe arụmọrụ ụwa na-adaghị adaba.
Ileghara ogo data na atụmatụ nyocha anya na-emepụtakarị nsonaazụ na-adịghị mma.
Map mmejuputa
Malite na nkọwa asụsụ dị larịị nke nsonaazụ ịchọrọ.
Họrọ otu metrik ịga nke ọma na otu ọnọdụ ọdịda tupu nnwale.
Gbaa obere onye na-anya ụgbọ elu nwere data nnọchite anya, ọ bụghị ihe ngosi ngosi na-egbu maramara.
Detuo ebe ndị Naive Bayes Classifiers na-enyere aka yana ebe ụzọ dị mfe ka mma.
Nọgide na-eme nchọpụta
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Ntuziaka na-esote
Nchọpụta ihe ize ndụ Bayes kacha nta
Ajụjụ a na-ajụkarị
What is Naive Bayes Classifiers?
Naive Bayes bụ ngwa ngwa, nhazi ọkwa nke puru omume wuru na Bayes' theorem nke na-eche na njirimara ọ bụla nwere onwe ya nyere klas ahụ. N'agbanyeghị echiche ahụ na-enweghị isi, ọ na-arụ ọrụ nke ọma maka ọrụ ederede dị ka nzacha spam.
Kedu ihe bụ isi echiche 'enweghị uche' na nhazi ọkwa Naive Bayes?
Ihe nlereanya ahụ na-eche na njirimara ọ bụla na-enye aka n'adabereghị na nsonaazụ enyere klas ahụ, na-ahapụ ya ka ọ mụbaa ohere nke njirimara ọ bụla.
Kedu usoro ọmụmụ Naive Bayes wuru na ya?
Ọ na-eji usoro Bayes iji gbanwee ihe gbasara puru omume na klaasị na ihe nwere ike ịbụ ohere dị n'azụ maka klaasị ọ bụla.
Kedu ihe kpatara na mmejuputa a na-ejikarị achịkọta ihe gbasara log-probabilities kama ịba ụba nke ihe gbasara omume?
Ịba ụba ọtụtụ ihe puru omume n'okpuru 1 nwere ike ịdaba na efu, yabụ iwere ndekọ na nchịkọta na-eme ka mgbakọ na mwepụ kwụsie ike.
Kedu nsogbu Laplace (gbakwunye-otu) smoothing na-edozi?
Na-enweghị ire ụtọ, okwu a na-ahụtụbeghị na klas na-enye klas ahụ ohere efu efu; tinye-otu ọnụ zere nke a.
Kedu ụdị Naive Bayes kacha dị n'okike maka njirimara ọnụ ọgụgụ na akwụkwọ?
Ụdị Multinomial Naive Bayes nwere ọgụgụ isi dị ka ugboro ole okwu ọ bụla pụtara, na-eme ka ọ bụrụ ọkọlọtọ maka ederede.